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This is really cool!
It looks like the length scales of the vectors don't match the originals though: https://www.ncl.ucar.edu/Applications/Images/vector_1_lg.png
I think this is because of more conceptual differences between streamplot (integrates forward or backward until some constraint) and curly vectors (length varies with vector magnitude). It's handled length normalization in the various approaches here, but I don't know how robust that is.
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This method of making curly vectors uses streamlines without arrows, finds their end points, and afixes length-0 quiver arrows to the ends. We may want to investigate a curly vector function in geocat-viz, but this demonstrates the recommended work around by matplotlib and will be useful to users for now.